A novel approach based on non-parametric resampling with interval analysis for large engineering project risks

摘要

The issue of risk assessment has been always the matter of debate in large engineering projects (LEPs). The assessment is an indispensable means for the projects to accomplish their objectives. It is firmly accepted that LEPs are particularly subject to more potential risks than other business activities because of their complexity, uncertainty and ambiguity. These characteristics are often conducive to small sample sizes of the gathered risk data in practice. Consequently, traditional statistical techniques cannot contribute significantly to analyze the risk data. The non-parametric resampling technique, namely bootstrap, has been used subsequently to solve numerous complicated problems and evaluate the accuracy of a parameter estimator in situations where commonly used techniques are not valid. It is also more natural, applicable and simple to estimate the risk data in an interval form under decision-making process by considering the concept of safety by professional experts in LEPs. Hence, in this paper, a new approach based on bootstrap technique with the interval analysis is presented in the context of the project risk assessment. The proposed approach not only plays an important role in reducing risk data and saving time but also is more economical. A real case study is conducted to illustrate the applicability of the approach. Finally, the comparison results indicate that the proposed approach outperforms the traditional technique in terms of the accuracy and efficiency.